Special issue of New Media & Society
We invite paper proposals for a special issue in the journal New Media & Society that will interrogate the functions and effects of algorithms in contemporary governance. Contributing to the current academic debate, the special issue seeks to conceptualize the notion of context in algorithmic governance by, first, perceiving of algorithmic governance as an activity taking place in a variety of contexts and aiming at investigating these contexts in a systematic manner. Second, by focusing not only on how algorithms are used as tools for governance, but also on how such tools can be governed – controlled and held to account – and what challenges such forms of governance imply. The use of algorithms in society can imply a moving of contestable issues from negotiable to non-negotiable spaces, thereby reducing agency and influence of human actors. Active recontextualizations can become an important tool to problematize such and other consequences of algorithmic governance and reveal possible unintended implications and effects.
The special issue builds upon a series of workshops (2019-2020) facilitated by a networking grant from The Joint Committee for Nordic Research Councils in the Humanities and Social Sciences (NOS-HS) coordinated at the University of Helsinki, that focused on the multiplicity of contexts in which algorithmic systems operate. Drawing upon the conceptual work conducted during the workshops, the special issue focuses on two key themes: multiplying the contexts of algorithmic governance and governing algorithms in context.
Multiplying the contexts of algorithmic governance
Articles are invited that explore how specific conditions impact upon the efficacy and perceived legitimacy of algorithms as tools for governance. In particular, contributions may direct attention to the manifold everyday practices through which algorithmic governance is effectuated and investigate the legal, political, cultural, economic, and technological frames that predispose and tacitly guide these. Through this focus, it becomes clear that algorithmic governance is not only a deeply contextual activity, but also an activity carried out within the frames of a multiplicity of different and often competing contexts. Identifying exactly which contexts matter when, in which ways, and to whom becomes an important task for the planning of algorithmic forms of governance in and through autonomous machine learning systems. At the same time, active recontextualization enables problematizing and resisting algorithmic governance in cases where it is perceived as illegitimate or biased.
Governing algorithms in context
Articles are invited that focus on the fact that algorithms at once govern, and are themselves governed by, either human or non-human agents. The increased use of algorithms in all areas of life makes the question of how to understand and sufficiently control such governing algorithms a timely and salient area of critical inquiry. Issues such as the complexity and opacity of algorithmic assessment and feedback systems as well as their growing autonomy and pervasiveness are important areas of research dedicated to improving the governance of algorithms. Articles could, for example, aim at facilitating new technical solutions, at raising public awareness, at informing practices of decision-makers and funding bodies, as well as at critically assessing cultural and other responses to the governance of algorithms.
We welcome both disciplinary and interdisciplinary perspectives and studies employing various social scientific methods, including comparative case-studies, ethnography, socio-legal studies, design studies, and historical inquiry. We particularly encourage studies that challenge the status quo, either through innovative (mixed method) methodologies or critical reflections on the state of the art. Papers could address, but are not limited to, the following questions:
- What are the different ‘realities’ constructed by the use of algorithms in governance? How do they play out across time and space?
- How do individuals – in private or organisational contexts – make sense of and respond to algorithmic governance?
- What are the similarities and differences in the deployment of algorithmic governance within public and private sectors?
- What are the challenges of developing effective strategies for governing algorithms at the intersection of law and technology?
- How can different publics be made aware of ‘algorithmic bads’, while still benefiting from ‘algorithmic goods’?
In sum, papers can either systematically tackle the contexts of algorithmic governance or investigate the governance of algorithms, identifying challenges that emerge in different governance contexts.
Daria Gritsenko, Assistant Professor in Russian Big Data Methodology, University of Helsinki. firstname.lastname@example.org
Annette Markham, Professor of Media & Communication, Digital Ethnography Research Centre, RMIT, Melbourne. email@example.com
Holger Pötzsch, Professor of Media- and Documentation Studies, UiT – The Arctic University of Norway. firstname.lastname@example.org
Mariëlle Wijermars, Assistant Professor in Cyber-Security and Politics, Maastricht University. email@example.com
- Extended abstract submission deadline: 30 June. Please submit here: https://elomake.helsinki.fi/lomakkeet/105716/lomake.html
- Invitation to submit full draft: 15 July
- Deadline for full papers: 31 October
Proposals of 750-1000 words should include an abstract and a short description explaining how the proposed paper relates to the special issue theme. Please submit your proposal through the submission form no later than June 30, 2020. Invited paper submissions will be due 31 October 2020 and will undergo peer review following the usual procedures of New Media & Society. Approximately 10-12 papers will be sent out for full review. Therefore, the invitation to submit a full article does not guarantee acceptance into the special issue. The special issue is scheduled for publication in early 2022, with online first publication expected from mid-2021 onwards.